1. Field of the Invention
The present invention relates to a method of detecting a message from a received signal in a digital communication system, and more particularly, to a method and apparatus of calculating a likelihood metric of a modulated digital signal.
2. Description of Related Art
In a digital communication system, each symbol constituting a message goes through a modulation process before its transmission. Modulation, as used here, has a broader meaning of a process converting a digital signal into a form which can be transmitted in a channel. The modulation is performed by loading a digital signal onto a carrier or a plurality of carriers. This is to give a certain variation to the carrier according to a digital value of the digital signal and to enable a receiving end to restore the original digital signal from the modulated signal based on the information of a modulation scheme.
Examples of digital modulation schemes include amplitude shift keying (ASK), phase shift keying (PSK) and frequency-shift keying (FSK). ASK changes an amplitude of a carrier signal according to a value of digital data. While ASK has a simple structure, a receiving end may not distinguish the difference in a signal level in an environment where a signal to noise ratio is low.
PSK and FSK have a better performance than ASK. PSK and FSK for representing binary data are referred to as binary PSK (BPSK) and binary FSK (BFSK). BPSK gives variation to a phase of a carrier by utilizing a binary symbol represented as ‘0’ and ‘1’. Namely, BPSK gives a variation to a carrier signal transmitted in a channel by changing a phase of a carrier by 180 degrees when a data value to be transmitted is changed from ‘0’ to ‘1’ or from ‘1’ to ‘0’, On the other hand, BFSK utilizes a frequency, not a phase. Namely, BFSK utilizes two carriers represented as sinusoidal waves of respectively different frequencies, in order to indicate ‘0’ and ‘1’.
However, BPSK and BFSK do not effectively utilize a frequency band. This is because BPSK represents only two signals with one carrier, and BFSK needs a frequency band which increases in proportion to a number of carrier signals. To solve the aforementioned problem, quadrature PSK (QPSK) is utilized as a modulation scheme. QPSK transmits four levels of data by altering a phase of the carrier into 4 different values having a 90 degree interval.
In a digital modulation, basic modulation schemes may be employed in combination. In particular, a modulation scheme based on changing both an amplitude and a phase is called quadrature amplitude modulation (QAM). QAM may produce signals of which amplitudes are identical but phases are different, signals of which phases are identical but amplitudes are different, and signals of which both phases and amplitudes are different. 16QAM, 64QAM and 256QAM are representative examples of QAM, and may represent 16, 64 and 256 different data values, respectively.
With respect to the modulated signal as described above, a receiving end restores an original message through processes of demodulation and detection. The demodulation is a restoration of a signal, while the detection is a process of detecting a digital value of the signal. In the case of BPSK and BFSK, detection of a message is relatively easy, for it only requires determining whether a value of received data corresponds to ‘0’ or ‘1’. However, in the case of QPSK or QAM, it is not easy to detect messages, because a large number of data symbols are densely allocated in a limited frequency band.
Accordingly, in this case, it is not clearly determined whether received data correspond to ‘0’ or ‘1’. Instead, a likelihood that an originally transmitted bit value of a received signal is ‘0’ or ‘1’ is determined. The determination method described above is called as a soft decision. In this instance, a detector output is called as a soft bit. More particularly, the soft decision is performed by calculating a likelihood metric of each bit. The likelihood metric is a value indicating a likelihood that a particular signal may have been transmitted with respect to a received signal.
FIG. 1 is a flowchart illustrating a conventional method of receiving a signal transmitted from a digital communication system.
As illustrated in FIG. 1, in operation 110, a receiving end converts a received signal to a frequency domain by using a fast Fourier transform (FFT) module. In operation 120, the receiving end calculates a channel estimate from the received signal in a frequency domain, the channel estimate is a value that the characteristic of a channel is estimated. In operation 130, the receiving end compensates a distortion of the received signal based on the channel estimate. In operation 140, the receiving end calculates a likelihood metric of the compensated received signal. In operation 150, the receiving end decodes data, which was encoded in a transmitting end, based on the calculated likelihood metric. As a final step, the receiving end detects an original message. As described above, calculating of the likelihood metric is performed before detecting the message. Accordingly, a performance of the likelihood metric calculation becomes an important factor in determining a performance of the message detection.
Hereinafter, a technical field where the present invention belongs, which is the conventional art of a likelihood metric calculation method, will be described in detail by taking an example of 16QAM and 64QAM.
FIGS. 2 and 3 are diagrams illustrating locations of message symbols included in 16QAM and 64QAM signals in a signal constellation. The conventional likelihood metric calculation method with respect to the modulated signal is characterized by calculating a complex distance between each symbol and a received signal in the signal constellation of FIGS. 2 and 3.
When Ck, which is a transmitted signal with respect to a kth symbol, passes through a channel having the characteristic of hk and is received with a noise component nk added, a received signal yk is represented as,yk=hkCk+nk  [Equation 1]
If a receiving end can perfectly estimate a channel, a distortion caused by the channel may be compensated by multiplying the received signal and a complex conjugate of a channel estimate. The compensated received signal rk, calculated according to the above mentioned method and normalized by a square of an absolute value of the channel estimate, is represented as,
                              r          k                =                                                                                                  h                    k                    *                                    ⁢                                      h                    k                                                                                                                                  h                      k                                                                            2                                            ⁢                              C                k                                      +                                                            h                  k                  *                                                                                                                h                      k                                                                            2                                            ⁢                              n                k                                              =                                                    C                k                            +                                                n                  ̑                                k                                      =                                          r                                  x                  ,                  k                                            +                              j                ⁢                                                                  ⁢                                  r                                      y                    ,                    k                                                                                                          [                  Equation          ⁢                                          ⁢          2                ]            
As is already known to those skilled in the related art, each symbol of 16QAM consists of four bits. A likelihood with respect to each symbol bit is represented as a random variable having a Gaussian distribution in an additive white Gaussian noise (AWGN) environment. In this instance, the AWGN environment is utilized for modeling a thermal noise of a general system. As an example, when a transmitting end transmits a bit corresponding to a value of either a ‘0’ or ‘1’, a likelihood of a 1st bit is represented as,
                                                                                          L                  k                                ⁡                                  (                                                            b                      1                                        ❘                    1                                    )                                            =                            ⁢                              {                                                                            1                                                                        πσ                                                      n                            ̑                                                    2                                                                                      ⁢                                          exp                      (                                              -                                                                                                            (                                                                                                r                                                                      y                                    ,                                    k                                                                                                  +                                                                  1                                                                      10                                                                                                                              )                                                        2                                                                                σ                                                          n                              ̑                                                        2                                                                                              )                                                        +                                                                                                                                        ⁢                                                      1                                                                  πσ                                                  n                          ̑                                                2                                                                              ⁢                                      exp                    (                                          -                                                                                                    (                                                                                          r                                                                  y                                  ,                                  k                                                                                            +                                                              3                                                                  10                                                                                                                      )                                                    2                                                                          σ                                                      n                            ̑                                                    2                                                                                      )                                                  }                            ,                                                                                                            L                  k                                ⁡                                  (                                                            b                      1                                        ❘                    0                                    )                                            =                            ⁢                              {                                                                            1                                                                        πσ                                                      n                            ̑                                                    2                                                                                      ⁢                                          exp                      (                                              -                                                                                                            (                                                                                                r                                                                      y                                    ,                                    k                                                                                                  -                                                                  1                                                                      10                                                                                                                              )                                                        2                                                                                σ                                                          n                              ̑                                                        2                                                                                              )                                                        +                                                                                                                                        ⁢                                                      1                                                                  πσ                                                  n                          ̑                                                2                                                                              ⁢                                      exp                    (                                          -                                                                                                    (                                                                                          r                                                                  y                                  ,                                  k                                                                                            -                                                              3                                                                  10                                                                                                                      )                                                    2                                                                          σ                                                      n                            ̑                                                    2                                                                                      )                                                  }                            .                                                          [                  Equation          ⁢                                          ⁢          3                ]            
In this instance, σ{circumflex over (n)}2 indicates a noise variance, and Lk(b1|0) indicates a likelihood when the transmitting end transmits ‘0’ with respect to the 1st bit-of the kth symbol. The ratio of Lk(b1|0) and Lk(b1|1) is referred to as a log likelihood ratio (LLR).
A method of calculating an LLR with respect to a kth symbol bit by using a likelihood value of each transmission bit data, which is shown in Equation 3, is represented as,
                                          LLR            k                    ⁡                      (                          b              1                        )                          =                  log          ⁢                                          ⁢                                                    L                k                            ⁡                              (                                                      b                    1                                    ❘                  0                                )                                                                    L                k                            ⁡                              (                                                      b                    1                                    ❘                  1                                )                                                                        [                  Equation          ⁢                                          ⁢          4                ]            
In the conventional art, a likelihood of the each bit is calculated on the basis of a distance between each symbol and the received signal in the signal constellation of FIG. 2. The LLR is calculated by using the likelihood value calculated as above and represented as,
                                                        LLR              k                        ⁡                          (                              b                1                            )                                ≅                                    max              (                                                -                                                                                    (                                                                              r                                                          y                              ,                              k                                                                                -                                                      1                                                          10                                                                                                      )                                            2                                                              σ                                              n                        ̑                                            2                                                                      ,                                  -                                                                                    (                                                                              r                                                          y                              ,                              k                                                                                -                                                      3                                                          10                                                                                                      )                                            2                                                              σ                                              n                        ̑                                            2                                                                                  )                        -                          max              (                                                -                                                                                    (                                                                              r                                                          y                              ,                              k                                                                                +                                                      1                                                          10                                                                                                      )                                            2                                                              σ                                              n                        ̑                                            2                                                                      ,                                  -                                                                                    (                                                                              r                                                          y                              ,                              k                                                                                +                                                      3                                                          10                                                                                                      )                                            2                                                              σ                                              n                        ̑                                            2                                                                                  )                                      =                                            min              (                                                                                          (                                                                        r                                                                                    y                              ,                              k                                                        ⁢                                                                                                                                                                +                                                  1                                                      10                                                                                              )                                        2                                                        σ                                          n                      ̑                                        2                                                  ,                                                                            (                                                                        r                                                      y                            ,                            k                                                                          +                                                  3                                                      10                                                                                              )                                        2                                                        σ                                          n                      ̑                                        2                                                              )                        -                          min              (                                                                                          (                                                                        r                                                      y                            ,                            k                                                                          -                                                  1                                                      10                                                                                              )                                        2                                                        σ                                          n                      ̑                                        2                                                  ,                                                                            (                                                                        r                                                      y                            ,                            k                                                                          -                                                  3                                                      10                                                                                              )                                        2                                                        σ                                          n                      ̑                                        2                                                              )                                =                                    min              ⁡                              (                                                      D                                          q                      ⁢                                                                                          ⁢                      2                                                        ,                                      D                                          q                      ⁢                                                                                          ⁢                      3                                                                      )                                      -                          min              ⁡                              (                                                      D                                          q                      ⁢                                                                                          ⁢                      0                                                        ,                                      D                                          q                      ⁢                                                                                          ⁢                      1                                                                      )                                                                        [                  Equation          ⁢                                          ⁢          5                ]            
In this instance,
                    D        qe            =                                                                                                  r                                      y                    ,                    k                                                  -                l                                                    2                    ⁢          and          ⁢                                          ⁢                      D            ie                          =                                                                        r                                  x                  ,                  k                                            -              l                                            2                      ,                            with          ⁢                                          ⁢          e                =        0            ;              l        =                  3                      10                                ,                  e        =        1            ;              l        =                  1                      10                                ,                  e        =        2            ;              l        =                  -                      1                          10                                            ,                  e        =        3            ;              l        =                  -                                    3                              10                                      .                                ⁢        When the same method is applied to other bits, a method of calculating an LLR for each bit of a 16QAM received signal may be represented as,LLRk(b0)=min(Dq0,Dq3)−min(Dq1,Dq2)LLRk(b1)=min(Dq2,Dq3)−min(Dq0,Dq1)LLRk(b2)=min(Di0,Di3)−min(Di1,Di2)LLRk(b3)=min(Di2,Di3)−min(Di0,Di1)  [Equation 6]When the same method is applied to a 64QAM signal, an LLR for each bit of the 6 bits constituting the 64QAM signal may be obtained by,LLRk(b0)=min(Dq0,Dq3,Dq4,Dq7)−min(Dq1,Dq2,Dq5,Dq6)LLRk(b1)=min(Dq0,Dq1,Dq6,Dq7)−min(Dq2,Dq3,Dq4,Dq5)LLRk(b2)=min(Dq4,Dq5,Dq6,Dq7)−min(Dq0,Dq1,Dq2,Dq3)LLRk(b3)=min(Di0,Di3,Di4,Di7)−min(Di1,Di2,Di5,Di6)LLRk(b4)=min(Di0,Di1,Di6,Di7)−min(Di2,Di3,Di4,Di5)  [Equation 7]In this instance,
            D      qe        =                                                                                  r                                  y                  ,                  k                                            -              l                                            2                ⁢        and        ⁢                                  ⁢                  D          ie                    =                                                            r                              x                ,                k                                      -            l                                    2              ,                    with        ⁢                                  ⁢        e            =      0        ;          l      =              7                  42                      ,            e      =      1        ;          l      =              5                  42                      ,            e      =      2        ;          l      =              3                  42                      ,            e      =      3        ;          l      =              1                  42                      ,            e      =      4        ;          l      =              -                  1                      42                                ,            e      =      5        ;          l      =              -                  3                      42                                ,            e      =      6        ;          l      =              -                  5                      42                                ,                    and        ⁢                                  ⁢        e            =      7        ;          l      =              -                              7                          42                                .                    
The conventional likelihood metric calculation method including the above described operations has the following problems.
First of all, a dividing operation or a divider is utilized in the operation of compensating distortion of a received signal based on a channel estimate, as shown in Equation 2. As is already known, the dividing by an arbitrary number other than a two's power makes the likelihood metric calculation more complicated, thereby deteriorating a calculation speed and increasing an embodiment cost.
Also, the conventional likelihood metric calculation method is based on a distance metric and indicates a location of each symbol as a fixed location in a signal constellation. Also, since the fixed symbol location becomes a standard for comparison when calculating a likelihood metric, an effect caused by a channel variation is not properly reflected. Accordingly, a likelihood metric calculation performance may be deteriorated. In particular, in the case of a wireless communication system in which a channel variation is severe, a satisfactory result may not be obtained.
Accordingly, the present invention proposes a new technology which can quickly and accurately calculate a likelihood metric of a received signal in digital communication systems including wireless communication systems.